2024 Healthcare Predictions: Harnessing AI

The institutional processes the healthcare system was built upon are fraught with inefficiencies. All too often, healthcare administrative staff are burdened by time-consuming, manual procedures—causing frustration among health plans, providers, and the patients they serve.

The convergence of these factors, in combination with staffing challenges and the growing complexity of the patient journey, have opened the door for transformative technology solutions that leverage the power of artificial intelligence (AI) and automation to help streamline administrative tasks, boost overall efficiency, and improve the patient experience. Availity is pleased to be at the forefront of this change – offering integrated, automated solutions that aim to revolutionize workflows and turn laborious tasks into prompt, actionable insights.

Below is a snapshot of the key areas where we expect significant advancement in 2024 and beyond.

Reducing Friction Between Payers and Providers in Pre-Service Workflows

The healthcare journey is complex, which is why companies such as Availity are laser-focused on developing integrated solutions that simplify administrative burdens and improve both provider and patient satisfaction. The adoption of automated solutions in pre-service processes can transform a manual process that previously required hours of work into a streamlined approach that, within minutes, makes it possible to surface fit-for-purpose data that is relevant and actionable. In 2024, we expect to further leverage automation technology to reduce payer/provider friction and burnout in pre-service workflows, with the ultimate goal of getting patients the right care in a faster manner.

Predictive Editing in Revenue Cycle Management

The increased adoption of AI in the clinical space has provided a glidepath for its application in revenue cycle management, where automation can bring efficiencies to onerous tasks such as denial management, pre-service eligibility, and authorizations. One of the most exciting use cases is the opportunity for predictive editing, which uses an AI algorithm that focuses on the subset of denials that are most likely to be avoidable and correctable. Through the application of responsible predictive editing technology, providers can reduce the administrative cost of reworking claims and enhance revenue cycle performance. This technology enables increased edit coverage by capturing complex, payer-specific edit scenarios beyond the scope of traditional front-end edit engines, while also minimizing the administrative effort required for maintaining manual rules and resulting in cost savings on implementation.

Revolutionizing Prior Authorizations with Responsible AI

There’s no denying that AI will continue to revolutionize healthcare organizations by introducing data-driven decisioning recommendations and predictive insights. Another major area where we have already seen and continue to expect rapid transformation is prior authorizations. The key to AI’s success in prior authorizations—or any other healthcare task—requires heightened responsibility from AI developers to design transparent and trustworthy AI systems that allow users to trace the reasoning behind AI-generated recommendations. By embracing patient data complexities and upholding the highest accountability, traceability, and transparency standards in AI tools, we can pave the way for a more advanced, streamlined, and patient-centric healthcare system.

What’s Next in Healthcare

Over the past year, we’ve seen an explosion of excitement in leveraging AI and other core automation technologies to eliminate some of healthcare’s inefficiencies that have historically impeded the exchange of critical administrative and clinical information throughout the patient journey. As we navigate the transformative landscape of healthcare in 2024, automated solutions that evolve intelligently and responsibly offer health plans and providers the potential for increased efficiency and effectiveness – limiting the time spent on mundane, repetitive tasks, so they can focus on driving better overall outcomes for patients.